This dissertation introduces a new probabilistic analysis method that scales to large and even infinite systems which are far out of reach of previous methods. The key idea is to approximate a given system by a smaller abstraction which is refined automatically until sufficient precision has been achieved. The thesis discusses the various foundational and practical challenges involved in developing this method, as well as its effectiveness in practice.
|Versandkostenfrei innerhalb Deutschlands|
Wollen auch Sie Ihre Dissertation veröffentlichen?